Re:Show HN: Word2Bits – Quantized Word Vectors
by iampims on Tuesday March 20, 2018 @03:05AM
(#16626494)
From the paper
> Figure 2 shows a visualisation of 800 dimensional 1 bit word vectors trained on English Wikipedia (2017). The top 100 closest and furthest word vectors to the target word vector are plotted. Distance is measured by dot product; every 5 word vectors are labelled. A turquoise line separates the 100 closest vectors to the target word from the 100 furthest vectors (labelled “...”). We see that there are qualitative similarities between word vectors whose words are related to each other.
> Figure 2 shows a visualisation of 800 dimensional 1 bit word vectors trained on English Wikipedia (2017). The top 100 closest and furthest word vectors to the target word vector are plotted. Distance is measured by dot product; every 5 word vectors are labelled. A turquoise line separates the 100 closest vectors to the target word from the 100 furthest vectors (labelled “...”). We see that there are qualitative similarities between word vectors whose words are related to each other.